5.1. Partial Dependence and Individual Conditional Expectation plots

When features are correlated, how many evaluation points used by a response curve fall outside a declared support region?

The evaluator generates a known joint distribution, independently computes response averages on a small grid and labels extrapolative points rather than interpreting them causally.

What you could produce

• A versioned minimal protocol, evaluator-owned test cases, and a comparison report with numerical/statistical uncertainty and failures.

Before you use it

• scikit-learn 1.9.1
• Compatible NumPy/SciPy and compiled dependencies; exact environment not prepared

Limits to keep in view

• No upstream example, source package, build hook or submitted code was executed.
• The current qualified pilot accepts only self-contained Python 3.13 with a 90-second deadline. This reference's package/runtime is not qualified for that path.
• The proposed protocol requires bounded resource estimates and an independently controlled evaluator before any scientific execution claim.

Source and permission context

scikit-learn documentation. 5.1. Partial Dependence and Individual Conditional Expectation plots. https://scikit-learn.org/stable/modules/partial_dependence.html; observed version 1.9.1 (observed documentation version; stable URL is mutable).

Rights need review. Review the scope and upstream conditions before reuse.

Still unresolved

• Third-party figures, linked papers, datasets and dependency licenses have not been assessed; no external content is copied into this catalog.